Simplify complex decisions by assigning weights and scores to your options.
Enter the number of choices you are evaluating (2-10).
Criteria and Weights
Name of the first evaluation factor.
Importance of this criterion (0.0 to 1.0). Sum of weights must equal 1.0.
Options and Scores
Name of the first choice.
Name of the second choice.
Name of the third choice.
Weighted Scores
—
Highest Weighted Score
Intermediate Results
Option A Total Score:—
Option B Total Score:—
Option C Total Score:—
Total Weights Sum:—
Key Assumptions
Number of Options:—
Criteria Analyzed:—
Weight Distribution: Equal (if not manually set to sum to 1.0)
How the Weighted Ranking Matrix is Calculated
Each criterion is assigned a weight reflecting its importance. Each option is then scored against each criterion. The weighted score for an option on a specific criterion is calculated as: (Option Score for Criterion) * (Criterion Weight). The total weighted score for an option is the sum of its weighted scores across all criteria. The option with the highest total weighted score is typically the preferred choice.
Formula: Total Weighted Score (Option N) = Σ [Score (Option N, Criterion i) * Weight (Criterion i)]
Option Performance Comparison
Visualizing the total weighted scores for each option.
Weighted Score Breakdown
Option / Criterion
Weight
Score
Weighted Score
What is a Weighted Ranking Matrix?
A {primary_keyword}, also known as a weighted decision matrix or Pugh matrix, is a powerful analytical tool used to evaluate and prioritize multiple options based on a set of predefined criteria. It allows decision-makers to systematically compare choices by assigning numerical weights to different factors and scoring each option against these factors. This structured approach helps to remove subjective bias and provides a quantifiable basis for making complex choices, whether in business, personal finance, or project management.
Who Should Use It?
Project managers selecting the best approach for a new initiative.
Business leaders choosing between strategic investments or product development paths.
Procurement teams evaluating different vendors or suppliers.
Individuals making significant personal decisions, like choosing a new car or a place to live.
Anyone needing to compare multiple alternatives objectively.
Common Misconceptions:
It guarantees the "perfect" choice: The matrix provides a data-driven recommendation, but it relies on the quality of input (criteria selection, weights, scores). Human judgment is still crucial.
It's overly complex: While it involves multiple steps, the underlying logic is straightforward, and tools like our {primary_keyword} calculator simplify the process significantly.
Weights must be complex fractions: Weights simply represent relative importance. They can be simple whole numbers or decimals that add up to a convenient total (like 100 or 1.0) to reflect priorities.
{primary_keyword} Formula and Mathematical Explanation
The core of the {primary_keyword} lies in a systematic calculation that converts qualitative preferences into quantitative scores. The process ensures that more important factors have a greater influence on the final ranking.
Step-by-Step Derivation:
Identify Options: List all the alternatives you are considering. These are the items you want to rank.
Define Criteria: Determine the key factors or attributes that are relevant to your decision. These should be specific and measurable where possible.
Assign Weights to Criteria: Assign a numerical weight to each criterion, indicating its relative importance. The sum of all weights should typically equal 1.0 (or 100%), ensuring a balanced representation of priorities. A higher weight signifies greater importance.
Score Each Option Against Each Criterion: For every option, assign a numerical score for each criterion. This scoring scale should be consistent across all options and criteria (e.g., 1-5, 1-10). Higher scores indicate better performance on that specific criterion.
Calculate Weighted Scores: For each option and each criterion, multiply the option's score by the criterion's weight. This gives you the "weighted score" for that specific combination. Formula: Weighted Score = Option Score × Criterion Weight
Calculate Total Weighted Score: Sum the weighted scores for each option across all criteria. This results in a single total score for each option. Formula: Total Weighted Score (Option N) = Σ [Score (Option N, Criterion i) × Weight (Criterion i)]
Rank Options: Rank the options based on their total weighted scores, from highest to lowest. The option with the highest total score is generally considered the most favorable based on the defined criteria and weights.
Variable Explanations:
Options: The different choices or alternatives being evaluated.
Criteria: The factors or attributes used to evaluate the options.
Weights (W): Numerical values assigned to each criterion, representing its importance relative to other criteria. The sum of all weights is usually normalized to 1.0.
Scores (S): Numerical ratings assigned to each option for each specific criterion, typically on a predefined scale.
Weighted Score: The product of an option's score for a criterion and that criterion's weight.
Total Weighted Score: The sum of all weighted scores for a single option across all criteria.
Variables Table:
Weighted Ranking Matrix Variables
Variable
Meaning
Unit
Typical Range
Number of Options
Quantity of choices being compared.
Count
2 – 10+
Number of Criteria
Quantity of factors used for comparison.
Count
3 – 15+
Criterion Weight (Wi)
Relative importance of Criterion i.
Decimal (or %)
0.0 to 1.0 (summing to 1.0)
Option Score (Sn,i)
Rating of Option n for Criterion i.
Score (e.g., 1-10)
1 to 10 (or other defined scale)
Weighted Score (WSn,i)
Contribution of Criterion i to Option n's total score.
Score Unit × Weight Unit
Depends on Score and Weight ranges
Total Weighted Score (TWSn)
Overall score for Option n.
Score Unit
Depends on Score and Weight ranges
Practical Examples (Real-World Use Cases)
Example 1: Choosing a New Laptop
A student needs a new laptop and has three options: Laptop A (High-end), Laptop B (Mid-range), and Laptop C (Budget). They define the criteria and weights:
Criteria & Weights: Performance (Weight: 0.4), Portability (Weight: 0.3), Battery Life (Weight: 0.2), Price (Weight: 0.1) – Sum = 1.0
Interpretation: Laptop B has the highest weighted score (7.7), making it the most suitable choice despite Laptop A's superior performance, due to the high importance of portability and a balanced consideration of other factors.
Example 2: Selecting a Cloud Service Provider
A tech startup is choosing between Cloud Provider X, Y, and Z. They prioritize reliability, cost, scalability, and support.
Criteria & Weights: Reliability (0.4), Cost (0.3), Scalability (0.2), Support (0.1) – Sum = 1.0
Scoring Scale: 1 (Worst) to 5 (Best)
Scores assigned:
Cloud Provider Scores
Criterion
Weight
Provider X Score
Provider Y Score
Provider Z Score
Reliability
0.4
4
5
3
Cost (Lower is better, requires inverse scoring or adjustment)
Interpretation: Provider X emerges as the top choice with a score of 3.9, indicating that its balance of high reliability and scalability, despite not being the cheapest, aligns best with the startup's priorities. This demonstrates how the {primary_keyword} helps weigh trade-offs.
How to Use This {primary_keyword} Calculator
Our Weighted Ranking Matrix Calculator is designed for ease of use, allowing you to quickly input your decision parameters and get immediate results.
Enter Number of Options: Start by specifying how many choices you are comparing.
Define Criteria and Weights:
For each criterion, enter its name (e.g., "Cost", "Features", "Ease of Use").
Assign a weight to each criterion reflecting its importance. The weights should ideally sum to 1.0 (e.g., 0.5, 0.3, 0.2). If they don't sum to 1.0, the calculator will note the total sum.
Name Your Options: Provide clear names for each of the options you are evaluating.
Input Scores: For each option, assign a score against each criterion. Use a consistent scale (e.g., 1-5 or 1-10) where a higher number means better performance for that criterion. Remember to consider if a factor like 'cost' should be scored inversely (lower cost = higher score).
View Results: The calculator will automatically update in real time.
The Main Result shows the option with the highest total weighted score.
Intermediate Results display the total score for each individual option.
The table provides a detailed breakdown of weighted scores for each criterion.
The chart offers a visual comparison of the total scores.
Copy or Reset: Use the "Copy Results" button to save the summary of your analysis, or "Reset" to start over with default values.
Decision-Making Guidance: The option with the highest total weighted score is your top-ranked choice based on your defined priorities. However, consider reviewing options with scores close to the top one, as small changes in weights or scores can alter the ranking. Also, ensure the criteria and weights truly reflect your decision-making context.
Key Factors That Affect {primary_keyword} Results
While the {primary_keyword} provides a structured method, several factors significantly influence its outcome:
Criterion Selection: The choice of criteria is paramount. Missing a crucial factor or including irrelevant ones will skew the results. Ensure criteria are comprehensive and directly related to the decision's goals.
Weight Assignment: This is arguably the most subjective part. Over- or under-weighting a criterion can disproportionately favor or penalize an option. Careful consideration of priorities is essential. For instance, if 'long-term growth potential' is critical for an investment, it should carry a higher weight than 'initial setup cost'.
Scoring Scale Consistency: Using a consistent and well-defined scoring scale (e.g., 1-10) across all options and criteria is vital. Inconsistent scoring introduces bias. Clearly define what each score point represents (e.g., '1 = Very Poor, 10 = Exceptional').
Subjectivity in Scoring: Even with a defined scale, assigning scores can involve subjectivity. Basing scores on objective data, expert opinions, or demonstrable evidence reduces this bias. For example, scoring a vendor's reliability should ideally be based on uptime statistics rather than a general feeling.
Interdependencies Between Criteria: Sometimes criteria are related. For instance, higher performance might correlate with higher cost. While the matrix handles this mathematically, acknowledging such relationships during the scoring phase can lead to more realistic assessments.
Normalizing Scores: For criteria where higher values are *worse* (like 'cost' or 'risk'), scores need to be inverted or normalized appropriately. For example, if Option A costs $100 (score 1) and Option B costs $50 (score 10), the matrix correctly reflects that lower cost is better. Failing to adjust these can lead to incorrect rankings.
Number of Options and Criteria: A large number of options or criteria can make the process cumbersome and potentially introduce errors. Simplifying the set where possible, or using pairwise comparisons within broader categories, can help manage complexity.
Dynamic Environment: Priorities and conditions can change. A decision made today might need re-evaluation if market conditions, personal needs, or business goals shift significantly. Regularly reviewing and updating the matrix might be necessary.
Frequently Asked Questions (FAQ)
Q1: What's the difference between a simple ranking and a weighted ranking matrix?
A simple ranking lists items based on a single factor or overall impression. A {primary_keyword} breaks down the decision into multiple criteria, assigns importance (weights) to each, and scores options against them, providing a more nuanced and objective comparison.
Q2: Should the weights always add up to 1.0?
It's a common convention to have weights sum to 1.0 (or 100%) for easy interpretation of relative importance. However, the calculation works even if they don't; the resulting total scores would simply be on a different scale. The key is consistency in how weights are assigned relative to each other.
Q3: How do I score criteria where a lower number is better (like cost)?
You have two main options:
1. Inverse Scoring: Assign higher scores to options with lower costs (e.g., lowest cost gets a 10, highest gets a 1).
2. Score and Invert Calculation: Score normally (higher cost = higher score) and then apply an inversion formula during calculation, like Inverted Score = Max Score + 1 – Original Score. Our calculator assumes direct scoring where higher is better; adjust your scoring accordingly.
Q4: Can I use negative weights or scores?
Generally, no. Weights represent importance, and scores represent performance. Both should be non-negative. Negative values would complicate the interpretation and undermine the logic of the matrix.
Q5: What if two options have the same total weighted score?
If scores are tied, it indicates they are equally favorable based on your current criteria and weights. You might need to:
Introduce a tie-breaker criterion.
Re-examine the weights or scores for subtle differences.
Use a more granular scoring scale.
Consider qualitative factors not captured in the matrix.
Q6: How granular should my criteria be?
Criteria should be specific enough to be scored meaningfully but not so granular that the matrix becomes unmanageable. For example, instead of just "Features," you might break it down into "Specific Feature A," "Specific Feature B," etc., if those are critical and distinct.
Q7: Can this matrix be used for personal decisions like choosing a job offer?
Absolutely. A {primary_keyword} is excellent for personal decisions. You can define criteria like Salary, Benefits, Commute Time, Work-Life Balance, Career Growth Opportunities, and assign weights based on your personal priorities.
Q8: How often should I update my weighted ranking matrix?
Update the matrix if the underlying decision context changes significantly. This could include shifts in priorities (weights), new information about the options (scores), or the emergence of new alternatives. For ongoing projects or strategic decisions, periodic reviews (e.g., quarterly or annually) are advisable.
SWOT Analysis TemplateA strategic planning tool to assess Strengths, Weaknesses, Opportunities, and Threats.
var currentOptionsCount = 3;
var currentCriteriaCount = 1;
function validateInput(id, min, max, isFloat = false) {
var input = document.getElementById(id);
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var value = input.value.trim();
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return true;
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function updateMatrixInputs() {
var numOptionsInput = document.getElementById('num_options');
if (!validateInput('num_options', 2, 10)) return;
var numOptions = parseInt(numOptionsInput.value);
var optionsList = document.getElementById('options-list');
var optionsSection = document.getElementById('options-section');
optionsList.innerHTML = "; // Clear existing option inputs
var headerRow = document.createElement('div');
headerRow.className = 'option-row';
for (var i = 1; i <= numOptions; i++) {
var optionNameDiv = document.createElement('div');
optionNameDiv.className = 'input-group option-input';
var label = document.createElement('label');
label.textContent = 'Option ' + i + ' Name:';
var input = document.createElement('input');
input.type = 'text';
input.id = 'option_name_' + i;
input.value = 'Option ' + String.fromCharCode(64 + i); // A, B, C…
input.setAttribute('oninput', 'updateMatrix()');
var small = document.createElement('small');
small.textContent = 'Name of the ' + i + ' option.';
var errorDiv = document.createElement('div');
errorDiv.id = 'option_name_' + i + '_error';
errorDiv.className = 'error-message';
optionNameDiv.appendChild(label);
optionNameDiv.appendChild(input);
optionNameDiv.appendChild(small);
optionNameDiv.appendChild(errorDiv);
headerRow.appendChild(optionNameDiv);
}
optionsList.appendChild(headerRow);
updateMatrix();
}
function addCriterionInput() {
currentCriteriaCount++;
var criteriaList = document.getElementById('criteria-list');
var criterionNameDiv = document.createElement('div');
criterionNameDiv.className = 'input-group criteria-input';
criterionNameDiv.innerHTML = `
Name of the ${currentCriteriaCount} evaluation factor.
`;
criteriaList.appendChild(criterionNameDiv);
var criterionWeightDiv = document.createElement('div');
criterionWeightDiv.className = 'input-group criteria-input';
criterionWeightDiv.innerHTML = `
Importance of this criterion (0.0 to 1.0). Sum of weights must equal 1.0.
`;
criteriaList.appendChild(criterionWeightDiv);
// Dynamically add score inputs for the new criterion
addScoreInputsForCriterion(currentCriteriaCount);
validateWeights();
updateMatrix();
}
function addScoreInputsForCriterion(criterionIndex) {
var optionsList = document.getElementById('options-list');
var numOptions = parseInt(document.getElementById('num_options').value);
// Add header for the new criterion scores if not already present
var scoreHeaderRow = document.querySelector('.score-header-row');
if (!scoreHeaderRow) {
scoreHeaderRow = document.createElement('div');
scoreHeaderRow.className = 'input-group score-header-row';
optionsList.insertBefore(scoreHeaderRow, optionsList.firstChild); // Insert at the beginning
}
var criterionHeader = document.createElement('div');
criterionHeader.className = 'criterion-header';
criterionHeader.innerHTML = `
Score from 1-10 (higher is better)
`;
scoreHeaderRow.appendChild(criterionHeader);
// Add score inputs for each option under the new criterion
for (var i = 1; i <= numOptions; i++) {
var optionRow = optionsList.querySelectorAll('.option-row')[0]; // Get the first row containing option names
if (!optionRow) { // If the row doesn't exist yet (e.g., first time adding criterion)
optionRow = document.createElement('div');
optionRow.className = 'option-row';
optionsList.appendChild(optionRow);
}
var scoreInputGroup = document.createElement('div');
scoreInputGroup.className = 'input-group option-score-input';
scoreInputGroup.innerHTML = `
Score for Option ${i} on Criterion ${criterionIndex}.
`;
// Find the corresponding option name input to insert the score input after it
var optionNameInput = optionRow.querySelector('#option_name_' + i);
if (optionNameInput) {
optionNameInput.parentNode.parentNode.insertBefore(scoreInputGroup, optionNameInput.parentNode.nextSibling);
} else {
// Fallback if the structure is unexpected
optionRow.appendChild(scoreInputGroup);
}
}
}
function removeCriterionInput() {
if (currentCriteriaCount > 1) {
var criteriaList = document.getElementById('criteria-list');
var weightInputToRemove = criteriaList.querySelector('#criterion_weight_' + currentCriteriaCount);
var nameInputToRemove = criteriaList.querySelector('#criterion_name_' + currentCriteriaCount);
if (weightInputToRemove && weightInputToRemove.parentNode) {
weightInputToRemove.parentNode.remove();
}
if (nameInputToRemove && nameInputToRemove.parentNode) {
nameInputToRemove.parentNode.remove();
}
// Remove corresponding score inputs
var optionsList = document.getElementById('options-list');
var scoreInputsToRemove = optionsList.querySelectorAll('[id$="_' + currentCriteriaCount + '"]');
scoreInputsToRemove.forEach(function(input) {
if (input.parentNode && input.parentNode.classList.contains('input-group')) {
input.parentNode.remove();
}
});
// Remove criterion header if it exists
var criterionHeader = document.querySelector('.score-header-row .criterion-header:last-child');
if (criterionHeader) {
criterionHeader.remove();
}
if (document.querySelectorAll('.score-header-row .criterion-header').length === 0) {
var headerRow = document.querySelector('.score-header-row');
if(headerRow) headerRow.remove();
}
currentCriteriaCount–;
validateWeights();
updateMatrix();
}
}
function updateMatrix() {
var numOptions = parseInt(document.getElementById('num_options').value);
var resultsTableBody = document.getElementById('results-table-body');
resultsTableBody.innerHTML = "; // Clear previous table rows
var optionTotalScores = {};
var weightedScoresData = {}; // To store data for table and chart
var allValid = true;
// — Input Validations —
if (!validateInput('num_options', 2, 10)) allValid = false;
for (var i = 1; i <= currentCriteriaCount; i++) {
if (!validateInput('criterion_name_' + i, null, null)) allValid = false; // Name validation
if (!validateInput('criterion_weight_' + i, 0, 1, true)) allValid = false;
}
for (var i = 1; i <= numOptions; i++) {
if (!validateInput('option_name_' + i, null, null)) allValid = false; // Name validation
for (var j = 1; j <= currentCriteriaCount; j++) {
if (!validateInput('score_' + i + '_' + j, 1, 10)) allValid = false;
}
}
// — Calculations (only if all inputs are valid) —
if (!allValid) {
displayResults('–', [], [], '–', '–', '–');
if (typeof window.myChart !== 'undefined') {
window.myChart.destroy(); // Destroy previous chart
window.myChart = undefined;
}
document.getElementById('results-table-body').innerHTML = '
Please correct the input errors above.
';
return;
}
var weightsSum = 0;
var criteriaWeights = [];
for (var i = 1; i <= currentCriteriaCount; i++) {
var weight = parseFloat(document.getElementById('criterion_weight_' + i).value);
criteriaWeights.push(weight);
weightsSum += weight;
}
document.getElementById('weights_sum').textContent = weightsSum.toFixed(2);
// — Option Score Calculation —
for (var i = 1; i <= numOptions; i++) {
var totalScore = 0;
var optionName = document.getElementById('option_name_' + i).value;
weightedScoresData[optionName] = { scores: [], weights: [] }; // Initialize for chart/table
for (var j = 1; j maxScore) {
maxScore = optionTotalScores[optionName];
bestOptionName = optionName;
}
}
// — Populate Results Display —
displayResults(maxScore.toFixed(2), optionTotalScores, weightedScoresData, numOptions, currentCriteriaCount);
// — Populate Table —
populateResultsTable(optionTotalScores, weightedScoresData);
// — Update Chart —
updateChart(optionTotalScores);
}
function populateResultsTable(optionTotalScores, weightedScoresData) {
var resultsTableBody = document.getElementById('results-table-body');
resultsTableBody.innerHTML = "; // Clear existing rows
var criteriaNames = [];
for(var i=1; i <= currentCriteriaCount; i++) {
criteriaNames.push(document.getElementById('criterion_name_' + i).value);
}
for (var optionName in optionTotalScores) {
var totalScore = optionTotalScores[optionName];
var row = resultsTableBody.insertRow();
// First cell: Option Name and Total Score
var cell1 = row.insertCell();
cell1.innerHTML = `${optionName}Total: ${totalScore.toFixed(2)}`;
// Second cell: Weight (Sum) – only for the first row header
var cell2 = row.insertCell();
if (resultsTableBody.rows.length === 1) { // If this is the first data row
cell2.innerHTML = `Weights Sum${document.getElementById('weights_sum').textContent}`;
} else {
cell2.innerHTML = "; // Empty for other rows
}
// Third cell: Score (Avg) – This interpretation is less common for WRM,
// often it's a breakdown per criterion. Let's adapt the table structure.
// Modified structure: Option | Criterion1 Weighted Score | Criterion2 Weighted Score | … | Total Score
// Rebuilding the table structure for clarity per criteria
// The initial table caption is "Weighted Score Breakdown" which implies summing up weighted scores per criterion.
// Let's rebuild the loop to reflect this.
}
// — Rebuild Table Row by Row for Criteria Breakdown —
resultsTableBody.innerHTML = "; // Clear again for the new structure
// Add header row for criteria names
var criteriaHeaderRow = resultsTableBody.insertRow();
var thOption = document.createElement('th');
thOption.textContent = 'Option';
criteriaHeaderRow.appendChild(thOption);
var thWeightSum = document.createElement('th');
thWeightSum.textContent = 'Weight Sum';
criteriaHeaderRow.appendChild(thWeightSum);
for(var i = 0; i < criteriaNames.length; i++) {
var thCrit = document.createElement('th');
thCrit.textContent = `${criteriaNames[i]} (W: ${criteriaWeights[i].toFixed(2)})`;
criteriaHeaderRow.appendChild(thCrit);
}
var thTotal = document.createElement('th');
thTotal.textContent = 'Total Score';
criteriaHeaderRow.appendChild(thTotal);
// Add data rows for each option
for (var optionName in optionTotalScores) {
var optionData = weightedScoresData[optionName];
var dataRow = resultsTableBody.insertRow();
var cellOptionName = dataRow.insertCell();
cellOptionName.textContent = optionName;
var cellWeightSum = dataRow.insertCell();
cellWeightSum.textContent = document.getElementById('weights_sum').textContent; // Display sum of weights
for (var i = 0; i < criteriaNames.length; i++) {
var cellWeightedScore = dataRow.insertCell();
// Calculate weighted score for this option and criterion
var score = optionData.scores[i];
var weight = optionData.weights[i];
var weightedScore = score * weight;
cellWeightedScore.textContent = weightedScore.toFixed(2);
}
var cellTotalScore = dataRow.insertCell();
cellTotalScore.innerHTML = `${optionTotalScores[optionName].toFixed(2)}`;
}
}
function displayResults(mainResult, intermediateScores, weightedScoresData, numOptions, numCriteria) {
document.getElementById('main-result').textContent = mainResult;
document.getElementById('assumed_options').textContent = numOptions;
document.getElementById('assumed_criteria_count').textContent = numCriteria;
var intermediateResultsHtml = ";
var optionNames = Object.keys(intermediateScores);
for (var i = 0; i < optionNames.length; i++) {
var optionName = optionNames[i];
var score = intermediateScores[optionName].toFixed(2);
intermediateResultsHtml += `${optionName} Total Score:${score}`;
}
// Ensure we have placeholders for scores even if calculation fails or is incomplete
var maxPossibleOptions = parseInt(document.getElementById('num_options').max);
for (var i = optionNames.length + 1; i <= maxPossibleOptions; i++) {
intermediateResultsHtml += `Option ${i} Total Score:—`;
}
document.querySelector('.intermediate-results').innerHTML = `
Intermediate Results
${intermediateResultsHtml}Total Weights Sum:${document.getElementById('weights_sum').textContent}`;
var assumptionsHtml = ";
for (var i = 0; i < optionNames.length; i++) {
assumptionsHtml += `Option ${i+1} Name: ${optionNames[i]}`;
}
document.querySelector('.key-assumptions').innerHTML = `
Key Assumptions
Number of Options: ${numOptions}Criteria Analyzed: ${numCriteria}Weight Distribution: ${document.getElementById('weights_sum').textContent === '1.00' ? 'Normalized (Sum=1.0)' : 'Not Normalized (Sum != 1.0)'}`;
if (mainResult === '–') {
document.getElementById('result-container').style.backgroundColor = '#6c757d';
document.getElementById('result-title').textContent = 'Calculation Pending';
} else {
document.getElementById('result-container').style.backgroundColor = '#28a745';
document.getElementById('result-title').textContent = 'Weighted Scores';
}
}
function updateChart(optionTotalScores) {
var ctx = document.getElementById('optionChart').getContext('2d');
// Destroy previous chart instance if it exists
if (window.myChart) {
window.myChart.destroy();
}
var labels = Object.keys(optionTotalScores);
var dataValues = Object.values(optionTotalScores);
// Assign colors dynamically, or use a predefined set
var backgroundColors = [
'rgba(0, 74, 153, 0.7)', // Primary blue
'rgba(40, 167, 69, 0.7)', // Success green
'rgba(255, 193, 7, 0.7)', // Warning yellow
'rgba(220, 53, 69, 0.7)', // Danger red
'rgba(108, 117, 125, 0.7)', // Secondary gray
'rgba(13, 202, 240, 0.7)' // Info cyan
];
var borderColors = [
'rgba(0, 74, 153, 1)',
'rgba(40, 167, 69, 1)',
'rgba(255, 193, 7, 1)',
'rgba(220, 53, 69, 1)',
'rgba(108, 117, 125, 1)',
'rgba(13, 202, 240, 1)'
];
// Ensure we have enough colors or cycle through them
var dataColors = labels.map(function(_, index) {
return backgroundColors[index % backgroundColors.length];
});
var borderDataColors = labels.map(function(_, index) {
return borderColors[index % borderColors.length];
});
window.myChart = new Chart(ctx, {
type: 'bar',
data: {
labels: labels,
datasets: [{
label: 'Total Weighted Score',
data: dataValues,
backgroundColor: dataColors,
borderColor: borderDataColors,
borderWidth: 1
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
scales: {
y: {
beginAtZero: true,
title: {
display: true,
text: 'Score'
}
},
x: {
title: {
display: true,
text: 'Options'
}
}
},
plugins: {
legend: {
display: false // Hide legend as only one dataset
},
title: {
display: true,
text: 'Comparison of Option Total Scores'
}
}
}
});
}
function validateWeights() {
var weightsSum = 0;
var allWeightsValid = true;
var weightInputs = [];
for(var i = 1; i 0.001) {
warningMessage.textContent = 'Warning: Weights do not sum to 1.0. Results will be relative.';
warningMessage.style.color = '#ffc107';
allWeightsValid = false; // Consider non-normalized sum as potentially problematic for interpretation
} else {
warningMessage.textContent = ";
warningMessage.style.color = 'green';
}
// Apply error styling to individual weight inputs if necessary
weightInputs.forEach(function(input) {
var errorElement = document.getElementById(input.id + '_error');
if (errorElement && errorElement.textContent !== ") {
input.style.borderColor = '#dc3545';
} else {
input.style.borderColor = '#ccc'; // Reset border if valid
}
});
return allWeightsValid; // Return true only if all individual weights are valid and sum is close to 1.0
}
function copyResults() {
var mainResult = document.getElementById('main-result').textContent;
var intermediateResultsElements = document.querySelectorAll('.intermediate-results p');
var intermediateResultsText = "";
intermediateResultsElements.forEach(function(p) {
intermediateResultsText += p.textContent + "\n";
});
var assumptionsElements = document.querySelectorAll('.key-assumptions p');
var assumptionsText = "";
assumptionsElements.forEach(function(p) {
assumptionsText += p.textContent + "\n";
});
var table = document.getElementById('results-table');
var tableText = "Weighted Score Breakdown:\n";
var tableRows = table.querySelectorAll('tr');
tableRows.forEach(function(row) {
var cells = row.querySelectorAll('th, td');
var rowText = Array.from(cells).map(function(cell) {
return cell.textContent.replace(/(\r\n|\n|\r)/gm, " ").trim(); // Clean up text
}).join('\t'); // Use tab for separation
tableText += rowText + "\n";
});
var resultString = `— Weighted Ranking Matrix Results —\n\n`;
resultString += `Primary Result: ${mainResult}\n`;
resultString += `\n${intermediateResultsText}\n`;
resultString += `\n${assumptionsText}\n`;
resultString += `\n${tableText}`;
navigator.clipboard.writeText(resultString).then(function() {
// Optional: Show a confirmation message
var copyButton = document.querySelector('button[onclick="copyResults()"]');
var originalText = copyButton.textContent;
copyButton.textContent = 'Copied!';
setTimeout(function() {
copyButton.textContent = originalText;
}, 1500);
}).catch(function(err) {
console.error('Failed to copy results: ', err);
// Fallback for environments without clipboard API or user denied permission
alert("Could not copy results automatically. Please select and copy manually:\n\n" + resultString);
});
}
function resetCalculator() {
// Reset number of options
document.getElementById('num_options').value = 3;
// Reset criteria inputs (keep first one, remove others)
currentCriteriaCount = 1;
var criteriaList = document.getElementById('criteria-list');
var criterionNameInputs = criteriaList.querySelectorAll('.criteria-input input[type="text"]');
var criterionWeightInputs = criteriaList.querySelectorAll('.criteria-input input[type="number"]');
document.getElementById('criterion_name_1').value = "Cost";
document.getElementById('criterion_weight_1').value = "0.40";
for (var i = criterionNameInputs.length – 1; i > 0; i–) {
if (criterionNameInputs[i].parentNode) criterionNameInputs[i].parentNode.remove();
}
for (var i = criterionWeightInputs.length – 1; i > 0; i–) {
if (criterionWeightInputs[i].parentNode) criterionWeightInputs[i].parentNode.remove();
}
// Reset options inputs
document.getElementById('option_name_1').value = "Option A";
document.getElementById('option_name_2').value = "Option B";
document.getElementById('option_name_3').value = "Option C";
// Remove extra option name inputs if any
var optionNameInputs = document.querySelectorAll('#options-list .option-name-input');
for (var i = optionNameInputs.length – 1; i >= 3; i–) {
optionNameInputs[i].remove();
}
// Remove score inputs dynamically generated
document.getElementById('options-list').querySelectorAll('.option-score-input').forEach(function(el) {
el.remove();
});
document.querySelectorAll('.score-header-row').forEach(function(el) {
el.remove();
});
// Re-initialize the matrix structure based on default num_options = 3
updateMatrixInputs();
// Add default score inputs for the initial state (3 options, 1 criterion)
addScoreInputsForCriterion(1); // Add scores for criterion 1
// Ensure default values are set for the initial criterion/scores
document.getElementById('criterion_name_1').value = "Cost";
document.getElementById('criterion_weight_1').value = "0.40";
for(var i=1; i<=3; i++) { // Default options A, B, C
document.getElementById('option_name_' + i).value = "Option " + String.fromCharCode(64 + i);
for (var j=1; j<=currentCriteriaCount; j++) { // Default scores
var scoreInput = document.getElementById('score_' + i + '_' + j);
if(scoreInput) scoreInput.value = '5';
}
}
// Validate and update the matrix display
validateWeights();
updateMatrix();
}
// Initialize calculator on load
document.addEventListener('DOMContentLoaded', function() {
// Set initial values and structure
currentOptionsCount = 3;
currentCriteriaCount = 1;
// Clear any existing criteria inputs beyond the first one
var criteriaList = document.getElementById('criteria-list');
var criterionInputs = criteriaList.querySelectorAll('.criteria-input');
for (var i = 1; i < criterionInputs.length; i++) {
criterionInputs[i].remove();
}
// Set initial criterion values
document.getElementById('criterion_name_1').value = "Cost";
document.getElementById('criterion_weight_1').value = "0.40";
// Initialize options and scores for default 3 options and 1 criterion
updateMatrixInputs(); // Sets up option name inputs for 3 options
addScoreInputsForCriterion(1); // Adds score inputs for the first criterion
// Set default scores for the initial setup
for (var i = 1; i <= 3; i++) {
document.getElementById('option_name_' + i).value = "Option " + String.fromCharCode(64 + i);
var scoreInput = document.getElementById('score_' + i + '_1');
if (scoreInput) scoreInput.value = '5'; // Default score
}
validateWeights();
updateMatrix(); // Calculate initial results
});
// Add event listeners for dynamic criteria addition/removal if needed
// (These buttons are not in the provided HTML, but would be necessary for full functionality)
// Example: document.getElementById('add-criterion-btn').addEventListener('click', addCriterionInput);
// Example: document.getElementById('remove-criterion-btn').addEventListener('click', removeCriterionInput);